“How do you discover something you didn’t know you were looking for? I’m looking for information on [a topic]—I don’t know what specifically, but I want to know as much as I can. Diffeo shows those non-obvious relationships,” said Geoffery Milstein, VP of Federal Programs at Diffeo.

Diffeo grew out of the Text Retrieval Conference Knowledge Base Acceleration project, which it organized for the National Institute of Standards and Technology and DARPA Memex. The company also won the grand prize last year in the National Geospatial-Intelligence Agency’s Disparate Data Challenge.

At GEOINT 2017, the company is demonstrating how it uses “collaborative machine intelligence,”—or AI—in algorithms to help accelerate the discovery of pertinent information during research.

What differentiates Diffeo is that its software operates seamlessly within a user’s normal work process, namely in applications like Microsoft Word or OneNote. As progress is made and data is added, the machine performs textual analysis to continuously learn about the user’s interests and what sorts of disparate information might be useful. The software then sends automatic queries to external and internal sources like databases, SharePoint repositories, and the internet, pulling together relevant information for the user.

“You don’t have to have ground-truth data. Every time the user interacts with the machine, it is reformulating its model,” Milstein said. “It’s not just another tool you have to learn.”

Additionally, Diffeo is showcasing its “knowledge boards” or graph displays, which perform gap analysis between working documents and, for example, a website the user has been frequenting in order to create visual representations of the data.